Learning about learning health systems: Strengthening theory through c ontinuous evaluation and improvement - Gremyr, Andreas; Seid, Michael; Margolis, Peter A.; Ramaswamy, Rohit (Learning Health Systems, 2025)
Introduction Learning Health Systems (LHSs) offer potential for transf orming healthcare through continuous learning and improvement. However , the current literature lacks a robust connection between theory and practice, limiting knowledge transferability across diverse healthcare environments. This article proposes a novel framework for integrating theorizing and continuous evaluation into LHSs, illustrated through t he case of the Bipolar Action Network (The Network). Methods We use a process of theorizing to structure how mid-range theory, program theor y and LHS design, development and evaluation can support improved prac tices and theories. We use the Conceptual Framework for Value-Creating Learning Health Systems as our initial mid-range theory, and the Bipo lar Action Network serves as an illustrative case. Results The framewo rk emphasizes continuous multi-level LHS theory refinement based on re al-world data, ensuring that both the system and its theoretical under pinnings evolve in response to new insights and challenges by connecti ng four steps: (1) Selecting an initial mid-range theory, (2) Creating a program theory for a specific LHS, (3) Evaluating LHS performance u sing operational data, and (4) Using evaluation findings to refine bot h the LHS program and mid-range theory. Conclusions This article contr ibutes to the field by offering a practical methodology for bridging t he gap between LHS theory and practice. By promoting ongoing theorizin g and evaluation, our framework aims to both enhance the effectiveness and adaptability of LHSs, as well as inform theory development. Chall enges remain, including resource intensity for data infrastructure and potential limitations in data quality or accessibility, which must be addressed to realize the full potential of LHSs as adaptive, theory-d riven systems.
Keywords: health services research; implementation science; learning health system; quality improvement